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of Irreproducible Research!

Author's title

Author

*Unverified author*

R Software Module

rwasp_smp.wasp

Title produced by software

Standard Deviation-Mean Plot

Date of computation

Fri, 29 Nov 2013 06:56:03 -0500

Cite this page as follows

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2013/Nov/29/t1385726178ecgbifne5hmg2j1.htm/, Retrieved Sun, 05 May 2024 21:47:11 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=229499, Retrieved Sun, 05 May 2024 21:47:11 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

120

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)

-       [Standard Deviation-Mean Plot] [] [2013-11-29 11:56:03] [40534ca708dbd0a01437b63d5245c315] [Current]

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Dataseries X:

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Histogram

Boxplots

-2.5
4.4
13.7
12.3
13.4
2.2
1.7
-7.2
-4.8
-2.9
-2.4
-2.5
-5.3
-7.1
-8
-8.9
-7.7
-1.1
4
9.6
10.9
13
14.9
20.1
10.8
11
3.8
10.8
7.6
10.2
2.2
-0.1
-1.7
-4.8
-9.9
-13.5
-18.1
-18
-15.7
-15.2
-15.1
-17.9
-14.5
-9.4
-4.2
-2.2
4.5
12.4
15.8
11.5
14.1
18.8
26.1
27.9
25.4
23.4
11.5
9.9
8.1
12.6
8.2
5.4
1
-2.9
-3.7
-7
-7.2
-11.8
-2.1
1.2
2.5
4.8
-6.6
-16
-22.7
-17.7
-18.2
-18.9
-16
-12.2
-17.1
-18.6
-17.5
-24.9

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	2 seconds
R Server	'Gertrude Mary Cox' @ cox.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 2 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=229499&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=229499&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=229499&T=0

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	2 seconds
R Server	'Gertrude Mary Cox' @ cox.wessa.net

Standard Deviation-Mean Plot
Section	Mean	Standard Deviation	Range
1	2.11666666666667	7.34486008695671	20.9
2	2.86666666666667	10.4689439715182	29
3	2.2	8.43951743557975	24.5
4	-9.45	10.0046807227236	30.5
5	17.0916666666667	6.97794686309966	19.8
6	-0.966666666666667	5.90459502626915	20
7	-17.2	4.6317088933489	18.3

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 2.11666666666667 & 7.34486008695671 & 20.9 \tabularnewline
2 & 2.86666666666667 & 10.4689439715182 & 29 \tabularnewline
3 & 2.2 & 8.43951743557975 & 24.5 \tabularnewline
4 & -9.45 & 10.0046807227236 & 30.5 \tabularnewline
5 & 17.0916666666667 & 6.97794686309966 & 19.8 \tabularnewline
6 & -0.966666666666667 & 5.90459502626915 & 20 \tabularnewline
7 & -17.2 & 4.6317088933489 & 18.3 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=229499&T=1

[TABLE]
[ROW][C]Standard Deviation-Mean Plot[/C][/ROW]
[ROW][C]Section[/C][C]Mean[/C][C]Standard Deviation[/C][C]Range[/C][/ROW]
[ROW][C]1[/C][C]2.11666666666667[/C][C]7.34486008695671[/C][C]20.9[/C][/ROW]
[ROW][C]2[/C][C]2.86666666666667[/C][C]10.4689439715182[/C][C]29[/C][/ROW]
[ROW][C]3[/C][C]2.2[/C][C]8.43951743557975[/C][C]24.5[/C][/ROW]
[ROW][C]4[/C][C]-9.45[/C][C]10.0046807227236[/C][C]30.5[/C][/ROW]
[ROW][C]5[/C][C]17.0916666666667[/C][C]6.97794686309966[/C][C]19.8[/C][/ROW]
[ROW][C]6[/C][C]-0.966666666666667[/C][C]5.90459502626915[/C][C]20[/C][/ROW]
[ROW][C]7[/C][C]-17.2[/C][C]4.6317088933489[/C][C]18.3[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=229499&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=229499&T=1

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

Standard Deviation-Mean Plot
Section	Mean	Standard Deviation	Range
1	2.11666666666667	7.34486008695671	20.9
2	2.86666666666667	10.4689439715182	29
3	2.2	8.43951743557975	24.5
4	-9.45	10.0046807227236	30.5
5	17.0916666666667	6.97794686309966	19.8
6	-0.966666666666667	5.90459502626915	20
7	-17.2	4.6317088933489	18.3

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	7.70179192770379
beta	0.0419821928470584
S.D.	0.0858585422802544
T-STAT	0.488969317811414
p-value	0.645555897050066

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 7.70179192770379 \tabularnewline
beta & 0.0419821928470584 \tabularnewline
S.D. & 0.0858585422802544 \tabularnewline
T-STAT & 0.488969317811414 \tabularnewline
p-value & 0.645555897050066 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=229499&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]7.70179192770379[/C][/ROW]
[ROW][C]beta[/C][C]0.0419821928470584[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0858585422802544[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.488969317811414[/C][/ROW]
[ROW][C]p-value[/C][C]0.645555897050066[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=229499&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=229499&T=2

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	7.70179192770379
beta	0.0419821928470584
S.D.	0.0858585422802544
T-STAT	0.488969317811414
p-value	0.645555897050066

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	2.22427778363797
beta	-0.0882161615044937
S.D.	0.112555152767573
T-STAT	-0.783759422251066
p-value	0.515262273395105
Lambda	1.08821616150449

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 2.22427778363797 \tabularnewline
beta & -0.0882161615044937 \tabularnewline
S.D. & 0.112555152767573 \tabularnewline
T-STAT & -0.783759422251066 \tabularnewline
p-value & 0.515262273395105 \tabularnewline
Lambda & 1.08821616150449 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=229499&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]2.22427778363797[/C][/ROW]
[ROW][C]beta[/C][C]-0.0882161615044937[/C][/ROW]
[ROW][C]S.D.[/C][C]0.112555152767573[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.783759422251066[/C][/ROW]
[ROW][C]p-value[/C][C]0.515262273395105[/C][/ROW]
[ROW][C]Lambda[/C][C]1.08821616150449[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=229499&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=229499&T=3

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	2.22427778363797
beta	-0.0882161615044937
S.D.	0.112555152767573
T-STAT	-0.783759422251066
p-value	0.515262273395105
Lambda	1.08821616150449

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = 12 ;

Parameters (R input):

par1 = 12 ;

R code (references can be found in the software module):

par1 <- as.numeric(par1)
(n <- length(x))
(np <- floor(n / par1))
arr <- array(NA,dim=c(par1,np))
j <- 0
k <- 1
for (i in 1:(np*par1))
{
j = j + 1
arr[j,k] <- x[i]
if (j == par1) {
j = 0
k=k+1
}
}
arr
arr.mean <- array(NA,dim=np)
arr.sd <- array(NA,dim=np)
arr.range <- array(NA,dim=np)
for (j in 1:np)
{
arr.mean[j] <- mean(arr[,j],na.rm=TRUE)
arr.sd[j] <- sd(arr[,j],na.rm=TRUE)
arr.range[j] <- max(arr[,j],na.rm=TRUE) - min(arr[,j],na.rm=TRUE)
}
arr.mean
arr.sd
arr.range
(lm1 <- lm(arr.sd~arr.mean))
(lnlm1 <- lm(log(arr.sd)~log(arr.mean)))
(lm2 <- lm(arr.range~arr.mean))
bitmap(file='test1.png')
plot(arr.mean,arr.sd,main='Standard Deviation-Mean Plot',xlab='mean',ylab='standard deviation')
dev.off()
bitmap(file='test2.png')
plot(arr.mean,arr.range,main='Range-Mean Plot',xlab='mean',ylab='range')
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Standard Deviation-Mean Plot',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Section',header=TRUE)
a<-table.element(a,'Mean',header=TRUE)
a<-table.element(a,'Standard Deviation',header=TRUE)
a<-table.element(a,'Range',header=TRUE)
a<-table.row.end(a)
for (j in 1:np) {
a<-table.row.start(a)
a<-table.element(a,j,header=TRUE)
a<-table.element(a,arr.mean[j])
a<-table.element(a,arr.sd[j] )
a<-table.element(a,arr.range[j] )
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Regression: S.E.(k) = alpha + beta * Mean(k)',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'alpha',header=TRUE)
a<-table.element(a,lm1$coefficients[[1]])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'beta',header=TRUE)
a<-table.element(a,lm1$coefficients[[2]])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'S.D.',header=TRUE)
a<-table.element(a,summary(lm1)$coefficients[2,2])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'T-STAT',header=TRUE)
a<-table.element(a,summary(lm1)$coefficients[2,3])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'p-value',header=TRUE)
a<-table.element(a,summary(lm1)$coefficients[2,4])
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable1.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'alpha',header=TRUE)
a<-table.element(a,lnlm1$coefficients[[1]])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'beta',header=TRUE)
a<-table.element(a,lnlm1$coefficients[[2]])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'S.D.',header=TRUE)
a<-table.element(a,summary(lnlm1)$coefficients[2,2])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'T-STAT',header=TRUE)
a<-table.element(a,summary(lnlm1)$coefficients[2,3])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'p-value',header=TRUE)
a<-table.element(a,summary(lnlm1)$coefficients[2,4])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Lambda',header=TRUE)
a<-table.element(a,1-lnlm1$coefficients[[2]])
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable2.tab')

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code